EMLasso.1l.param: Collect parameters to EMLasso.1l into one list

In EMLasso: Fit (logistic) LASSO when there is missing data in the predictors

Description

Collect parameters to EMLasso.1l into one list

Usage

  EMLasso.1l.param(ds, out, lambda,
    nrOfSamplesPerMDRow = 10,
    rowsToUseForFit = seq(nrow(ds)),
    firstTimeCompleter = marginalCompleter(),
    imputeDs2FitDsProperties = normalImputationConversion(),
    fitPredictor = GLoMo, family = "binomial",
    convergenceChecker = convergenceCheckCreator(),
    postProcess = postProcessEMLasso1l, verbosity = 0,
    extraLog = function(...) { })

  ## S3 method for class 'EMLasso.1l.param'
x[i]

  ## S3 method for class 'EMLasso.1l.param'
 length(x)

Arguments

ds	see EMLasso.1l
out	see EMLasso.1l
lambda	see EMLasso.1l
nrOfSamplesPerMDRow	see EMLasso.1l
rowsToUseForFit	see EMLasso.1l
firstTimeCompleter	see EMLasso.1l
imputeDs2FitDsProperties	see EMLasso.1l
fitPredictor	see EMLasso.1l
family	see EMLasso.1l
convergenceChecker	see EMLasso.1l
postProcess	see EMLasso.1l
verbosity	The higher this value, the more levels of progress and debug information is displayed (note: in R for Windows, turn off buffered output)
extraLog	see EMLasso.1l
x	EMLasso.1l.param object
i	integer indexer

Value

object of class "EMLasso.1l.param" having all these parameters as named members

Note

created for use in run.parallel

Author(s)

Nick Sabbe [e-mail]

See Also

run.parallel, EMLasso.1l

EMLasso.1l

Examples

aDfr<-generateTypicalIndependentDfr(numCat=10, numCnt=10, numObs=100, catProbs=rep(1/3,3),
rcnt=typicalRandomNorm, doShuffle=TRUE, verbosity=1)

outlins<- -mean(aDfr$cnt1)+aDfr$cnt1+2*(aDfr$cat1=="b")
outprobs<-expit(outlins)
y<-factor(sapply(outprobs, function(prob){sample(c("no", "yes"), 1, prob=c(1-prob,prob))}))

aDfr.MD<-randomNA(aDfr, 0.01, verbosity=1)
emlcvparm<-EMLasso.1l.param(aDfr.MD, y, lambda=0.05, nrOfSamplesPerMDRow=7, verbosity=10)
aDfr<-numdfr(generateTypicalIndependentDfr(100, 100, 150, doShuffle=FALSE))
y<-as.factor(rbinom(150, 1, 0.5))
emlcvparm<-EMLasso.1l.param(aDfr, y, lambda=0.05, nrOfSamplesPerMDRow=7, verbosity=10)
emlcvparm[1]
aDfr<-numdfr(generateTypicalIndependentDfr(100, 100, 150, doShuffle=FALSE))
y<-as.factor(rbinom(150, 1, 0.5))
emlcvparm<-EMLasso.1l.param(aDfr, y, lambda=0.05, nrOfSamplesPerMDRow=7, verbosity=10)
length(emlcvparm)

EMLasso documentation built on May 2, 2019, 5:49 p.m.